Executive Summary : | The research proposes an IoT-enabled system for crop cultivation, integrating artificial intelligence AI and machine learning ML. The system uses sensors to assess soil suitability for agriculture, predicting crop viability based on factors like soil properties, land topography, and socio-economic factors. The system also develops a machine learning-based Decision Support System (DSS) to optimize crop selection. The system also focuses on developing efficient irrigation and fertilization aids, enhancing crop yields and sustainability. The integration of IoT and ML in agriculture could revolutionize traditional practices and contribute to global food security. This purpose is to develop a comprehensive IoT and ML-based tool for land suitability and climate suitability analysis for multi crop management in the Devikulangara Panchayat in Alappuzha district, Kerala. The project involves a systematic field survey, data analysis, model design, and application development using Python programming. The goal is to address challenges faced by Indian agricultural sectors, such as soil health, irrigation, and seed quality, and provide advanced technical support to improve farming practices. The project aims to improve the resilience of farming communities and improve their farming practices. |